More plotting with ggplot2

class: center, middle, inverse, title-slide

# More plotting with ggplot2
### Kevin Stachelek
### 2019/03/18 (updated: 2019-03-19)

---

## Install required packages

```r
# Load the ggplot2 package
install.packages("ggplot2")
install.packages("magrittr") # important so that we can use %>%!
install.packages("gapminder")
install.packages("dplyr")
```

## Load required packages

```r
# Load the ggplot2 package
library(ggplot2)
library(magrittr) # important so that we can use %>%!
library(gapminder)
library(dplyr)
```

---

### Explore the mtcars data frame with `head()`
<table>
 <thead>
  <tr>
   <th style="text-align:left;">   </th>
   <th style="text-align:right;"> mpg </th>
   <th style="text-align:left;"> cyl </th>
   <th style="text-align:right;"> disp </th>
   <th style="text-align:right;"> hp </th>
   <th style="text-align:right;"> drat </th>
   <th style="text-align:right;"> wt </th>
   <th style="text-align:right;"> qsec </th>
   <th style="text-align:right;"> vs </th>
   <th style="text-align:right;"> am </th>
   <th style="text-align:right;"> gear </th>
   <th style="text-align:right;"> carb </th>
   <th style="text-align:left;"> fcyl </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Mazda RX4 </td>
   <td style="text-align:right;"> 21.0 </td>
   <td style="text-align:left;"> 6 </td>
   <td style="text-align:right;"> 160 </td>
   <td style="text-align:right;"> 110 </td>
   <td style="text-align:right;"> 3.90 </td>
   <td style="text-align:right;"> 2.620 </td>
   <td style="text-align:right;"> 16.46 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:left;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Mazda RX4 Wag </td>
   <td style="text-align:right;"> 21.0 </td>
   <td style="text-align:left;"> 6 </td>
   <td style="text-align:right;"> 160 </td>
   <td style="text-align:right;"> 110 </td>
   <td style="text-align:right;"> 3.90 </td>
   <td style="text-align:right;"> 2.875 </td>
   <td style="text-align:right;"> 17.02 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:left;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Datsun 710 </td>
   <td style="text-align:right;"> 22.8 </td>
   <td style="text-align:left;"> 4 </td>
   <td style="text-align:right;"> 108 </td>
   <td style="text-align:right;"> 93 </td>
   <td style="text-align:right;"> 3.85 </td>
   <td style="text-align:right;"> 2.320 </td>
   <td style="text-align:right;"> 18.61 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:left;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Hornet 4 Drive </td>
   <td style="text-align:right;"> 21.4 </td>
   <td style="text-align:left;"> 6 </td>
   <td style="text-align:right;"> 258 </td>
   <td style="text-align:right;"> 110 </td>
   <td style="text-align:right;"> 3.08 </td>
   <td style="text-align:right;"> 3.215 </td>
   <td style="text-align:right;"> 19.44 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:left;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Hornet Sportabout </td>
   <td style="text-align:right;"> 18.7 </td>
   <td style="text-align:left;"> 8 </td>
   <td style="text-align:right;"> 360 </td>
   <td style="text-align:right;"> 175 </td>
   <td style="text-align:right;"> 3.15 </td>
   <td style="text-align:right;"> 3.440 </td>
   <td style="text-align:right;"> 17.02 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 2 </td>
   <td style="text-align:left;"> 8 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Valiant </td>
   <td style="text-align:right;"> 18.1 </td>
   <td style="text-align:left;"> 6 </td>
   <td style="text-align:right;"> 225 </td>
   <td style="text-align:right;"> 105 </td>
   <td style="text-align:right;"> 2.76 </td>
   <td style="text-align:right;"> 3.460 </td>
   <td style="text-align:right;"> 20.22 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:left;"> 6 </td>
  </tr>
</tbody>
</table>

---

### Explore the mtcars data frame with `str()`

```r
str(mtcars)
```

```
## 'data.frame':	32 obs. of  12 variables:
##  $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
##  $ cyl : Factor w/ 3 levels "4","6","8": 2 2 1 2 3 2 3 1 1 2 ...
##  $ disp: num  160 160 108 258 360 ...
##  $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
##  $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
##  $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
##  $ qsec: num  16.5 17 18.6 19.4 17 ...
##  $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
##  $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
##  $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
##  $ carb: num  4 4 1 1 2 1 4 2 2 4 ...
##  $ fcyl: Factor w/ 3 levels "4","6","8": 2 2 1 2 3 2 3 1 1 2 ...
```

---

### Build a simple plot

```r
ggplot(mtcars, aes(x = cyl, y = mpg)) +
  geom_point()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-5-1.png)

---

### Axes aesthetics

```r
ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-6-1.png)

---

### Color aesthetics

```r
ggplot(mtcars, aes(x = wt, y = mpg, color = disp)) +
  geom_point()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-7-1.png)

---

### Size aesthetics

```r
ggplot(mtcars, aes(x = wt, y = mpg, size = disp)) +
  geom_point()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-8-1.png)

---

### One common error to avoid

```r
ggplot(mtcars, aes(x = wt, y = mpg, shape = disp)) +
  geom_point()
```

```r
table(mtcars$disp)
```

```
## 
##  71.1  75.7  78.7    79  95.1   108 120.1 120.3   121 140.8   145 146.7 
##     1     1     1     1     1     1     1     1     1     1     1     1 
##   160 167.6   225   258 275.8   301   304   318   350   351   360   400 
##     2     2     1     1     3     1     1     1     1     1     2     1 
##   440   460   472 
##     1     1     1
```

The _types_ of variables (i.e. columns) are important
---

### Let's look at another dataset

```r
# Explore the diamonds data frame with str()
str(diamonds)
```

```
## Classes 'tbl_df', 'tbl' and 'data.frame':	53940 obs. of  10 variables:
##  $ carat  : num  0.23 0.21 0.23 0.29 0.31 0.24 0.24 0.26 0.22 0.23 ...
##  $ cut    : Ord.factor w/ 5 levels "Fair"<"Good"<..: 5 4 2 4 2 3 3 3 1 3 ...
##  $ color  : Ord.factor w/ 7 levels "D"<"E"<"F"<"G"<..: 2 2 2 6 7 7 6 5 2 5 ...
##  $ clarity: Ord.factor w/ 8 levels "I1"<"SI2"<"SI1"<..: 2 3 5 4 2 6 7 3 4 5 ...
##  $ depth  : num  61.5 59.8 56.9 62.4 63.3 62.8 62.3 61.9 65.1 59.4 ...
##  $ table  : num  55 61 65 58 58 57 57 55 61 61 ...
##  $ price  : int  326 326 327 334 335 336 336 337 337 338 ...
##  $ x      : num  3.95 3.89 4.05 4.2 4.34 3.94 3.95 4.07 3.87 4 ...
##  $ y      : num  3.98 3.84 4.07 4.23 4.35 3.96 3.98 4.11 3.78 4.05 ...
##  $ z      : num  2.43 2.31 2.31 2.63 2.75 2.48 2.47 2.53 2.49 2.39 ...
```

---

###  We can build up a new plot following the same 'recipe' every time

+ add data (diamonds)

+ specify aesthetics (x axis and y axis inside `aes`)

+ add a geom object (`geom_point`)

```r
# Add geom_point() with +
ggplot(diamonds, aes(x = carat, y = price))  +
  geom_point()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-12-1.png)

---

### We can layer additional `geoms` one after another

```r
# Add geom_point() and geom_smooth() with +
ggplot(diamonds, aes(x = carat, y = price)) +
  geom_point() +
  geom_smooth()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-13-1.png)

---

### Let's recreate that plot

![](advanced_ggplot2_files/figure-html/unnamed-chunk-14-1.png)

```r
# 1 - The plot you created in the previous exercise
ggplot(diamonds, aes(x = carat, y = price)) +
  geom_point() +
  geom_smooth()
```

---

### Plotting only the trend-line

![](advanced_ggplot2_files/figure-html/unnamed-chunk-16-1.png)

```r
# 2 - Copy the above command but show only the smooth line
ggplot(diamonds, aes(x = carat, y = price)) +
  geom_smooth()
```

---

### Plotting separate lines for each diamond clarity value

![](advanced_ggplot2_files/figure-html/unnamed-chunk-18-1.png)

```r
# 3 - Copy the above command and assign the correct value to col in aes()
ggplot(diamonds, aes(x = carat, y = price, color = clarity)) +
  geom_smooth()
```

---

### Color points by clarity

![](advanced_ggplot2_files/figure-html/unnamed-chunk-20-1.png)

```r
# 4 - Keep the color settings from previous command. Plot only the points with argument alpha.
ggplot(diamonds, aes(x = carat, y = price, color = clarity)) +
  geom_point(alpha = 0.4)
```

---

### plots can be created in two different steps using the `+` symbol

```r
# Create the object containing the data and aes layers: dia_plot
dia_plot <- ggplot(diamonds, aes(x = carat, y = price))

# Add a geom layer with + and geom_point()
dia_plot + geom_point()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-22-1.png)
---

### aesthetics can be 'scoped' to a specific `geom` object

```r
# Add the same geom layer, but with aes() inside
dia_plot + geom_point(aes(color = clarity))
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-23-1.png)

---

### Basic scatter plot

![](advanced_ggplot2_files/figure-html/unnamed-chunk-24-1.png)

```r
# 2 - Expand dia_plot by adding geom_point() with alpha set to 0.2
dia_plot <- dia_plot + geom_point(alpha = 0.2)
print(dia_plot)
```

---

### Plot trendlines per group

![](advanced_ggplot2_files/figure-html/unnamed-chunk-26-1.png)

```r
# 3 - Plot dia_plot with additional geom_smooth() with se set to FALSE
dia_plot + geom_smooth(se = FALSE)
```

* `se` allows to specify confidence intervals

---

### Plot trendline by clarity

![](advanced_ggplot2_files/figure-html/unnamed-chunk-28-1.png)
--

```r
# 4 - Copy the command from above and add aes() with the correct mapping to geom_smooth()
dia_plot + geom_smooth(aes(col = clarity), se = FALSE)
```

---

# _Base R_ plotting

---

#### take a look at built-in `iris` dataset

```r
knitr::kable(head(iris), format = "html")
```

<table>
 <thead>
  <tr>
   <th style="text-align:right;"> Sepal.Length </th>
   <th style="text-align:right;"> Sepal.Width </th>
   <th style="text-align:right;"> Petal.Length </th>
   <th style="text-align:right;"> Petal.Width </th>
   <th style="text-align:left;"> Species </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 5.1 </td>
   <td style="text-align:right;"> 3.5 </td>
   <td style="text-align:right;"> 1.4 </td>
   <td style="text-align:right;"> 0.2 </td>
   <td style="text-align:left;"> setosa </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 4.9 </td>
   <td style="text-align:right;"> 3.0 </td>
   <td style="text-align:right;"> 1.4 </td>
   <td style="text-align:right;"> 0.2 </td>
   <td style="text-align:left;"> setosa </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 4.7 </td>
   <td style="text-align:right;"> 3.2 </td>
   <td style="text-align:right;"> 1.3 </td>
   <td style="text-align:right;"> 0.2 </td>
   <td style="text-align:left;"> setosa </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 4.6 </td>
   <td style="text-align:right;"> 3.1 </td>
   <td style="text-align:right;"> 1.5 </td>
   <td style="text-align:right;"> 0.2 </td>
   <td style="text-align:left;"> setosa </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 5.0 </td>
   <td style="text-align:right;"> 3.6 </td>
   <td style="text-align:right;"> 1.4 </td>
   <td style="text-align:right;"> 0.2 </td>
   <td style="text-align:left;"> setosa </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 5.4 </td>
   <td style="text-align:right;"> 3.9 </td>
   <td style="text-align:right;"> 1.7 </td>
   <td style="text-align:right;"> 0.4 </td>
   <td style="text-align:left;"> setosa </td>
  </tr>
</tbody>
</table>

---

### a simple base R plot

```r
plot(iris$Sepal.Length, iris$Sepal.Width)
points(iris$Petal.Length, iris$Petal.Width, col = "red")
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-31-1.png)

---

### Limitations of Base Plotting

1. Plot doesn't get redrawn (this is similar to `matplotlib` in python)

2. Plot is drawn as an image

3. Need to manually add legend

4. No unified framework for plotting

---

### More about Base plots

```r
# Plot the correct variables of mtcars
plot(mtcars$wt, mtcars$mpg, col = mtcars$cyl)
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-32-1.png)

---

### More about Base plots

```r
# Change cyl inside mtcars to a factor
mtcars$fcyl <- as.factor(mtcars$cyl)

# Make the same plot as in the first instruction
plot(mtcars$wt, mtcars$mpg, col = mtcars$fcyl)
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-33-1.png)

---
### More about Base plots

```r
# Use lm() to calculate a linear model and save it as carModel
carModel <- lm(mpg ~ wt, data = mtcars)

# Basic plot
mtcars$cyl <- as.factor(mtcars$cyl)
plot(mtcars$wt, mtcars$mpg, col = mtcars$cyl)

# Call abline() with carModel as first argument and set lty to 2
abline(carModel, lty = 2)
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-34-1.png)

---

### The same plot using `ggplot2`

```r
# Plot 1: add geom_point() to this command to create a scatter plot
ggplot(mtcars, aes(x = wt, y = mpg, col = cyl)) +
  geom_point()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-35-1.png)

---

### The same plot using `ggplot2`

```r
# Plot 2: include the lines of the linear models, per cyl
ggplot(mtcars, aes(x = wt, y = mpg, col = cyl)) +
  geom_point() +
  geom_smooth(aes(group = 1), method = "lm", se = FALSE, linetype = 2)
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-36-1.png)

---

### The same plot using `ggplot2`

```r
# Plot 3: include a lm for each group in the dataset
ggplot(mtcars, aes(x = wt, y = mpg, col = cyl)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE) +
  geom_smooth(aes(group = 1), method = "lm", se = FALSE, linetype = 2)
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-37-1.png)

---

# Let's talk about _tidy_ data!

### ggplot2 usually works with _tidy_ data

There are three interrelated rules which make a dataset tidy:

Each variable must have its own column.
    Each observation must have its own row.
    Each value must have its own cell.

![tidy-data](tidy-1.png)

---

###  two types of data: 'wide' and 'long'

<table>
 <thead>
  <tr>
   <th style="text-align:right;"> Length </th>
   <th style="text-align:right;"> Width </th>
   <th style="text-align:left;"> Species </th>
   <th style="text-align:left;"> Part </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 1.4 </td>
   <td style="text-align:right;"> 0.2 </td>
   <td style="text-align:left;"> setosa </td>
   <td style="text-align:left;"> Petal </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 1.4 </td>
   <td style="text-align:right;"> 0.2 </td>
   <td style="text-align:left;"> setosa </td>
   <td style="text-align:left;"> Petal </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 1.3 </td>
   <td style="text-align:right;"> 0.2 </td>
   <td style="text-align:left;"> setosa </td>
   <td style="text-align:left;"> Petal </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 1.5 </td>
   <td style="text-align:right;"> 0.2 </td>
   <td style="text-align:left;"> setosa </td>
   <td style="text-align:left;"> Petal </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 1.4 </td>
   <td style="text-align:right;"> 0.2 </td>
   <td style="text-align:left;"> setosa </td>
   <td style="text-align:left;"> Petal </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 1.7 </td>
   <td style="text-align:right;"> 0.4 </td>
   <td style="text-align:left;"> setosa </td>
   <td style="text-align:left;"> Petal </td>
  </tr>
</tbody>
</table>

* tidy Data is usually 'long'

---

### Tidy data makes code cleaner and therefore more reliable

```r
# Option 1
ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) +
  geom_point() +
  geom_point(aes(x = Petal.Length, y = Petal.Width), col = "red")

# Option 2
ggplot(iris.long, aes(x = Length, y = Width, col = Part)) +
  geom_point()
```
---

### Advantages of ggplot in comparison to base

1. The legend gets taken care of

2. The axis labels are legible

3. The plot can be __iterated on__

---

### So how we make data tidy?

## Use `tidyr` and `dplyr`!

```r
install.packages("nycflights13")
install.packages("tidyr")
```

```r
library(tidyr)
library(nycflights13)
```

---

### Gather

![gather](gather.png)

---

### Gather

```r
ds <- nycflights13::airports %>% 
  gather(lat, lon, key = "coordinate", value = "value")
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> faa </th>
   <th style="text-align:left;"> name </th>
   <th style="text-align:right;"> alt </th>
   <th style="text-align:right;"> tz </th>
   <th style="text-align:left;"> dst </th>
   <th style="text-align:left;"> tzone </th>
   <th style="text-align:left;"> coordinate </th>
   <th style="text-align:right;"> value </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> 04G </td>
   <td style="text-align:left;"> Lansdowne Airport </td>
   <td style="text-align:right;"> 1044 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
   <td style="text-align:left;"> lat </td>
   <td style="text-align:right;"> 41.13047 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06A </td>
   <td style="text-align:left;"> Moton Field Municipal Airport </td>
   <td style="text-align:right;"> 264 </td>
   <td style="text-align:right;"> -6 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/Chicago </td>
   <td style="text-align:left;"> lat </td>
   <td style="text-align:right;"> 32.46057 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06C </td>
   <td style="text-align:left;"> Schaumburg Regional </td>
   <td style="text-align:right;"> 801 </td>
   <td style="text-align:right;"> -6 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/Chicago </td>
   <td style="text-align:left;"> lat </td>
   <td style="text-align:right;"> 41.98934 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06N </td>
   <td style="text-align:left;"> Randall Airport </td>
   <td style="text-align:right;"> 523 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
   <td style="text-align:left;"> lat </td>
   <td style="text-align:right;"> 41.43191 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 09J </td>
   <td style="text-align:left;"> Jekyll Island Airport </td>
   <td style="text-align:right;"> 11 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
   <td style="text-align:left;"> lat </td>
   <td style="text-align:right;"> 31.07447 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 0A9 </td>
   <td style="text-align:left;"> Elizabethton Municipal Airport </td>
   <td style="text-align:right;"> 1593 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
   <td style="text-align:left;"> lat </td>
   <td style="text-align:right;"> 36.37122 </td>
  </tr>
</tbody>
</table>

---

### Spread

![spread](spread.png)

---

### Spread

```r
ds <- ds %>% 
  tidyr::spread(coordinate, value, c("lat", "lon"))
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> faa </th>
   <th style="text-align:left;"> name </th>
   <th style="text-align:right;"> alt </th>
   <th style="text-align:right;"> tz </th>
   <th style="text-align:left;"> dst </th>
   <th style="text-align:left;"> tzone </th>
   <th style="text-align:left;"> lat </th>
   <th style="text-align:left;"> lon </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> 04G </td>
   <td style="text-align:left;"> Lansdowne Airport </td>
   <td style="text-align:right;"> 1044 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
   <td style="text-align:left;"> 41.1304722 </td>
   <td style="text-align:left;"> -80.6195833 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06A </td>
   <td style="text-align:left;"> Moton Field Municipal Airport </td>
   <td style="text-align:right;"> 264 </td>
   <td style="text-align:right;"> -6 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/Chicago </td>
   <td style="text-align:left;"> 32.4605722 </td>
   <td style="text-align:left;"> -85.6800278 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06C </td>
   <td style="text-align:left;"> Schaumburg Regional </td>
   <td style="text-align:right;"> 801 </td>
   <td style="text-align:right;"> -6 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/Chicago </td>
   <td style="text-align:left;"> 41.9893408 </td>
   <td style="text-align:left;"> -88.1012428 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06N </td>
   <td style="text-align:left;"> Randall Airport </td>
   <td style="text-align:right;"> 523 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
   <td style="text-align:left;"> 41.431912 </td>
   <td style="text-align:left;"> -74.3915611 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 09J </td>
   <td style="text-align:left;"> Jekyll Island Airport </td>
   <td style="text-align:right;"> 11 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
   <td style="text-align:left;"> 31.0744722 </td>
   <td style="text-align:left;"> -81.4277778 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 0A9 </td>
   <td style="text-align:left;"> Elizabethton Municipal Airport </td>
   <td style="text-align:right;"> 1593 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
   <td style="text-align:left;"> 36.3712222 </td>
   <td style="text-align:left;"> -82.1734167 </td>
  </tr>
</tbody>
</table>

---

### Separate

![separate](separate.png)

---

### Separate

```r
ds2 <- nycflights13::airports %>% 
  tidyr::separate(tzone, into = c("country", "city"), sep = "/")
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> faa </th>
   <th style="text-align:left;"> name </th>
   <th style="text-align:right;"> lat </th>
   <th style="text-align:right;"> lon </th>
   <th style="text-align:right;"> alt </th>
   <th style="text-align:right;"> tz </th>
   <th style="text-align:left;"> dst </th>
   <th style="text-align:left;"> country </th>
   <th style="text-align:left;"> city </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> 04G </td>
   <td style="text-align:left;"> Lansdowne Airport </td>
   <td style="text-align:right;"> 41.13047 </td>
   <td style="text-align:right;"> -80.61958 </td>
   <td style="text-align:right;"> 1044 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America </td>
   <td style="text-align:left;"> New_York </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06A </td>
   <td style="text-align:left;"> Moton Field Municipal Airport </td>
   <td style="text-align:right;"> 32.46057 </td>
   <td style="text-align:right;"> -85.68003 </td>
   <td style="text-align:right;"> 264 </td>
   <td style="text-align:right;"> -6 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America </td>
   <td style="text-align:left;"> Chicago </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06C </td>
   <td style="text-align:left;"> Schaumburg Regional </td>
   <td style="text-align:right;"> 41.98934 </td>
   <td style="text-align:right;"> -88.10124 </td>
   <td style="text-align:right;"> 801 </td>
   <td style="text-align:right;"> -6 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America </td>
   <td style="text-align:left;"> Chicago </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06N </td>
   <td style="text-align:left;"> Randall Airport </td>
   <td style="text-align:right;"> 41.43191 </td>
   <td style="text-align:right;"> -74.39156 </td>
   <td style="text-align:right;"> 523 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America </td>
   <td style="text-align:left;"> New_York </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 09J </td>
   <td style="text-align:left;"> Jekyll Island Airport </td>
   <td style="text-align:right;"> 31.07447 </td>
   <td style="text-align:right;"> -81.42778 </td>
   <td style="text-align:right;"> 11 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America </td>
   <td style="text-align:left;"> New_York </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 0A9 </td>
   <td style="text-align:left;"> Elizabethton Municipal Airport </td>
   <td style="text-align:right;"> 36.37122 </td>
   <td style="text-align:right;"> -82.17342 </td>
   <td style="text-align:right;"> 1593 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America </td>
   <td style="text-align:left;"> New_York </td>
  </tr>
</tbody>
</table>

---

### Unite

![unite](unite.png)

---

### Unite

```r
ds2 <- ds2 %>% 
  tidyr::unite(country, city, col = "tzone", sep = "/")
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> faa </th>
   <th style="text-align:left;"> name </th>
   <th style="text-align:right;"> lat </th>
   <th style="text-align:right;"> lon </th>
   <th style="text-align:right;"> alt </th>
   <th style="text-align:right;"> tz </th>
   <th style="text-align:left;"> dst </th>
   <th style="text-align:left;"> tzone </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> 04G </td>
   <td style="text-align:left;"> Lansdowne Airport </td>
   <td style="text-align:right;"> 41.13047 </td>
   <td style="text-align:right;"> -80.61958 </td>
   <td style="text-align:right;"> 1044 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06A </td>
   <td style="text-align:left;"> Moton Field Municipal Airport </td>
   <td style="text-align:right;"> 32.46057 </td>
   <td style="text-align:right;"> -85.68003 </td>
   <td style="text-align:right;"> 264 </td>
   <td style="text-align:right;"> -6 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/Chicago </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06C </td>
   <td style="text-align:left;"> Schaumburg Regional </td>
   <td style="text-align:right;"> 41.98934 </td>
   <td style="text-align:right;"> -88.10124 </td>
   <td style="text-align:right;"> 801 </td>
   <td style="text-align:right;"> -6 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/Chicago </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 06N </td>
   <td style="text-align:left;"> Randall Airport </td>
   <td style="text-align:right;"> 41.43191 </td>
   <td style="text-align:right;"> -74.39156 </td>
   <td style="text-align:right;"> 523 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 09J </td>
   <td style="text-align:left;"> Jekyll Island Airport </td>
   <td style="text-align:right;"> 31.07447 </td>
   <td style="text-align:right;"> -81.42778 </td>
   <td style="text-align:right;"> 11 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 0A9 </td>
   <td style="text-align:left;"> Elizabethton Municipal Airport </td>
   <td style="text-align:right;"> 36.37122 </td>
   <td style="text-align:right;"> -82.17342 </td>
   <td style="text-align:right;"> 1593 </td>
   <td style="text-align:right;"> -5 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> America/New_York </td>
  </tr>
</tbody>
</table>

---

### Modifying aesthetics

+ everything in `aes` is an aesthetic mapping (this includes x-axis and y-axis)

+ we can modify these `aes` with some specific options

+ let's modify the x-axis aesthetic!

+ standard position
+ `fill` position (proportional)
+ `dodge` position (horizontally stacked position)

![](advanced_ggplot2_files/figure-html/unnamed-chunk-52-1.png)

---

# Other Types of Plots

### Load Data

```r
gm_2007 <- gapminder %>%
  filter(year == 2007)
```

###  Load (More) Data

```r
by_year_continent <- gapminder %>%
  group_by(year, continent) %>%
  summarize(totalPop = sum(pop),
            meanLifeExp = mean(lifeExp))
```

---

# Line plots

change over time

```r
ggplot(by_year_continent, aes(x = year, y = totalPop, color = continent, height = 3)) +
* geom_line() +
  expand_limits(y = 0)
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-55-1.png)

---

# Bar plots

comparing over several categories

```r
ggplot(by_continent, aes(x = continent, y = meanLifeExp)) +
* geom_col()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-57-1.png)

---

# histograms

distribution of a single numeric variable

```r
ggplot(gm_2007, aes(x = lifeExp)) +
* geom_histogram()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-58-1.png)

---

# It's important to manage the binwidth of a histogram

```r
ggplot(gm_2007, aes(x = lifeExp)) +
* geom_histogram(binwidth = 5)
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-59-1.png)

---

# box plots

distribution of several numeric variables

```r
ggplot(gm_2007, aes(x = continent, y = lifeExp)) +
* geom_boxplot()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-60-1.png)

---

# Histogram vs Box Plot

.pull-left[

```r
hist_plot <- ggplot(gm_2007, aes(x = lifeExp)) +
* geom_histogram()

hist_plot
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-61-1.png)
]

.pull-right[

```r
ggplot(gm_2007, aes(x = continent, y = lifeExp)) +
* geom_boxplot()
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-62-1.png)
]

---

# How to Print to a File

### Three ways:

### ggsave

### graphicsdevice

### manual

---

# ggsave

#### ggsave defaults to the last printed plot

```r
ggsave("test_histogram.pdf")
```

#### otherwise you can specify a plot object as the second argument

```r
ggsave("test_histogram2.pdf", plot = hist_plot)
```

---

# graphicsdevice (pdf, png, jpg, etc.)

#### *Warning* The plot needs to be *printed*, not just created within the graphics device

```r
pdf("test_histogram3.pdf")
hist_plot
dev.off()
```

```
## png 
##   2
```

---

# Manually

```r
# can use the rstudio viewer pane
print(hist_plot)
```

![](advanced_ggplot2_files/figure-html/unnamed-chunk-66-1.png)